New Rotation-Invariant Texture Analysis Technique Using Radon Transform and Hidden Markov Models
نویسندگان
چکیده
منابع مشابه
Rotation invariant texture characterization and retrieval using steerable wavelet-domain hidden Markov models
We present a new statistical model for characterizing texture images based on wavelet-domain hidden Markov models. With a small number of parameters, the new model captures both the subband marginal distributions and the dependencies across scales and orientations of the wavelet descriptors. Applying to the steerable pyramid, once it is trained for an input texture image, the model can be easil...
متن کاملRadon Transform application for rotation invariant texture analysis using Gabor filters
This paper presents a new approach of rotation invariant texture analysis. Robust rotation invariant textures are important for digital image libraries and multimedia database. Here a method for application of rotation variant Traditional Gabor Filter (TGF) for rotation invariant texture analysis is presented. The orientation of the texture is determined using radon transformation. Once the rot...
متن کاملRotation and gray-scale transform-invariant texture classification using spiral resampling, subband decomposition, and hidden Markov model
This paper proposes a new texture classification algorithm that is invariant to rotation and gray-scale transformation. First, we convert two-dimensional (2-D) texture images to one-dimensional (1-D) signals by spiral resampling. Then, we use a quadrature mirror filter (QMF) bank to decompose sampled signals into subbands. In each band, we take high-order autocorrelation functions as features. ...
متن کاملTexture Analysis Using Modified Discrete Radon Transform
In this paper, we address the problem of the rotationinvariant texture analysis. For this purpose, we first present a modified version of the discrete Radon transform whose performance, including accuracy and processing time, is significantly better than the conventional transform in direction estimation and categorization of textural images. We then utilize this transform with a rotated versio...
متن کاملWavelet-Based Texture Analysis and Synthesis Using Hidden Markov Models
Wavelet-domain hidden Markov models (HMMs), in particular hidden Markov tree (HMT), were recently proposed and applied to image processing, where it was usually assumed that three subbands of the 2-D discrete wavelet transform (DWT), i.e. HL, LH, and HH, are independent. In this paper, we study wavelet-based texture analysis and synthesis using HMMs. Particularly, we develop a new HMM, called H...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2008
ISSN: 0916-8532,1745-1361
DOI: 10.1093/ietisy/e91-d.12.2906